Artificial Intelligence popularly known as AI is the new thing in our world. The Trend, The Buzz Word, The new tag line for technological advancement. Generative AI has become the new social media trend. The internet is filled with AI generated literature, images and even AI generated songs. The latest “Studio Ghibli” trend is the testament to this frenzy. But like everything in this world, Generative AI has numerous dark sides and the environmental implications are one of them. Behind every AI-generated poem, picture, or song lies an immense network of data centers consuming vast amounts of electricity, water, and rare earth minerals. The training of large AI models can generate significant carbon emissions, sometimes comparable to those produced by multiple cars over their entire lifetime. These environmental consequences, coupled with emerging legal and regulatory challenges, demand a closer examination. Understanding both the promise and the pitfalls of Generative AI is essential if we are to embrace innovation without sacrificing sustainability.

Understanding The Environmental Challenge:

Generative AI might feel intangible — just algorithms churning out text, images, and music — but behind the scenes, it is anything but weightless. Every AI-generated poem, photo, or code snippet is powered by vast data centers consuming enormous amounts of electricity and water. The process of training these models can emit as much carbon as the lifetime emissions of several cars, tying digital innovation to a very real, and very physical, environmental cost. Most large scale AI deployments are housed in data centres. According to an article by UNEP, The electronics they house rely on a staggering amount of grist: making a 2kg computer requires 800kg of raw materials.

The rare earth elements used for making microchips are often derived in environmentally destructive ways. Hazardous substances like mercury and lead are produced as electronic waste.

Data Centres use water during construction and during operations to cool down the electronic components. That is a problem when parts of humanity still lack access to water for basic survival. A request made through ChatGPT, an AI-based virtual assistant, consumes 10 times the electricity of a Google Search, reported the International Energy Agency.

India Centric Viewpoint:

While we have discussed the universal environmental challenges and implications of the rise of Generative AI. The question of the hour is: What does it mean for a developing nation like India?

India’s burgeoning AI sector is significantly impacting the environment, particularly in terms of energy consumption and water usage.According to Mercom India, Data centers, essential for AI operations, consumed approximately 139 billion kWh of electricity in June 2023 alone . This demand is projected to increase, with AI expected to account for 19% of data center power demand by 2028 . Simultaneously, according to Mordor Intelligence, data center water consumption in India is anticipated to rise from 150.3 billion liters in 2025 to 358.7 billion liters by 2030 . These centers are often situated in regions already facing water scarcity, exacerbating local environmental stresses . The environmental footprint of AI is further compounded by the rapid growth of data centers, which are projected to become the fourth-largest global emitter of greenhouse gases by 2030, potentially emitting up to 2.5 billion tons of CO₂ equivalent annually . In response, India is exploring sustainable practices, such as integrating renewable energy sources into data center operations, to mitigate these environmental impacts.

Legal Framework For Ai Data Centres In India

The rapid proliferation of AI-driven data centers in India presents a multifaceted environmental challenge. These facilities are highly energy-intensive, with over 260 operational data centers whose electricity consumption is projected to increase substantially in the coming decade, potentially placing additional strain on the national power grid. In addition to electricity demands, data centers require significant volumes of water for cooling purposes, frequently in regions already subject to water scarcity, thereby accentuating the urgency of sustainable water management strategies. The accelerated obsolescence of AI hardware further contributes to substantial electronic waste, which is regulated under the E-Waste (Management and Handling) Rules, 2011, mandating proper collection, recycling, and disposal. While existing frameworks, including energy efficiency guidelines promulgated by the Bureau of Energy Efficiency and green building standards recommended by the Indian Green Building Council, provide avenues for mitigating environmental impact, these measures remain largely advisory, and AI-specific regulatory mechanisms are still in the process of development. Collectively, these considerations highlight the imperative for the adoption of comprehensive sustainability practices in India’s AI sector to reconcile technological advancement with environmental stewardship.

From Generative Ai To Sustainability

To address the environmental challenges posed by AI-driven data centers in India, a multifaceted and proactive approach is essential, informed both by domestic priorities and global best practices. Priority should be given to the adoption of energy-efficient technologies, including advanced cooling systems, server optimization, and energy management software, alongside the integration of renewable energy sources such as solar and wind power to reduce dependence on fossil fuels(Mercom India). Concurrently, water conservation strategies must be implemented, including closed-loop cooling systems, rainwater harvesting, and wastewater recycling, particularly in regions already experiencing water scarcity, aligning with the objectives of the National Water Mission. Effective management of electronic waste is equally critical; strengthening enforcement of the E-Waste (Management and Handling) Rules, 2011, alongside incentivizing recycling and refurbishment of AI hardware, can reduce environmental contamination and promote a circular economy. On a global scale, nations such as the European Union and the United States are implementing strict energy efficiency standards, carbon reporting requirements, and green certification programs for data centers, providing benchmarks that India can adapt to its context.

Furthermore, research and innovation should be leveraged to develop low-energy AI models, algorithm optimization techniques, and novel cooling technologies, ensuring that technological advancement occurs in harmony with environmental sustainability. By integrating domestic measures with insights drawn from global best practices, India can reduce the ecological footprint of AI, meet international sustainability benchmarks, and foster a technology sector that is both innovative and environmentally responsible. On an Individual level, Awareness towards AI should be increased. People should use AI responsibly and consciously. The multifaceted consequences of using Generative AI should be known to individuals for responsible decision making.

Conclusion

Finally, like every coin has two sides, AI too has a good and a bad side.It simplifies research and studies for professionals, students and academicians but it also raises environmental and legal issues. The destructive effect on the environment, corrosion of human intellect to misuse of deepfake, Many instances testifying the drawbacks of AI have emerged.The high energy usage, water consumption, and electronic waste produced by AI-based infrastructure are massive challenges that require collective international action and cooperation.Elucidating ways through which nations can address these environmental repercussions by embracing energy-efficient technologies, incorporating renewable energy, enforcing strict water conservation measures, and enhancing electronic waste management. In addition, a proper legal framework should be established to regulate and monitor the use of Artificial Intelligence. Focus on Research and Development as well as investment in low energy AI models, high performance cooling techniques as a sustainable approach by the counties can support technological advancement and environmental care . Finally, this is a global opportunity to prove that technological advancement and environmental preservation are not mutually exclusive. Preemptive action now will enable the development of an AI-fueled future that is both technologically sophisticated and environmentally sound, leading to advancement which is rewarding for the society without any drawbacks or implications.